|Publication number||US4991087 A|
|Application number||US 07/233,601|
|Publication date||Feb 5, 1991|
|Filing date||Aug 18, 1988|
|Priority date||Aug 19, 1987|
|Also published as||CA1291574C, EP0304302A2, EP0304302A3|
|Publication number||07233601, 233601, US 4991087 A, US 4991087A, US-A-4991087, US4991087 A, US4991087A|
|Inventors||Forbes J. Burkowski, Marke S. Krebs|
|Original Assignee||Burkowski Forbes J, Krebs Marke S|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (6), Referenced by (158), Classifications (11), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
1. Field of the Invention
This invention relates to a data retrieval system and, in particular, to a method of storing data on and retrieving data from a database using a signature file that is divided into subsets, the signature file being automatically created as the data is stored.
2. Description of the Prior Art
Data storage and retrieval systems are known. With the creation of larger and larger databases and the increased use thereof, it is becoming increasingly important to have an accurate method of storing and retrieving the data in a minimum amount of time. It is also important to be able to add information to an existing database without making extensive amendments to the existing information.
In many known databases, the information is highly organized as a carefully indexed structure resident on a storage medium such as a disk. When a portion of the data is to be retrieved, the system makes use of this indexing information in order to locate the required data which may be embedded in a huge collection of similar data items. Indexing information is stored in an extra file. There are various ways of establishing said index. One possible approach is the use of a signature file, the other is the use of an inverted file. The latter approach is often used since it provides fast retrieval but it has two significant shortcomings:
(a) the size of an inverted file is extremely large, being 20% to 100% of the size of the text file itself;
(b) when new data is to be entered into the database, the inverted file must be changed and the highly structured nature of the file makes modification of said file a very time consuming process since significant portions of the file must be altered.
While signature files provide extremely fast update capabilities, they are usually not the index strategy of choice since the retrieval time can be very slow. The slow retrieval time is caused by the scanning of the entire signature file and this is a very time consuming endeavour because the required transfer time from the disk will usually be of a very lengthy duration. The invention to be described uses signature files but with a strategy that make them very competitive with the inverted file approach. Rather than scanning the entire file, a subset of it is scanned instead. This will significantly lower the access time and if the system is carefully designed the modification time is still kept fairly low.
Of course, data can always be retrieved by scanning the entire database (avoiding the use of index files) but that is extremely time consuming and therefore prohibitively expensive.
When the data storage device is a write once optical disk, an update problem occurs with this technology as it is impossible to write information onto a particular area of the optical disk more than once. Therefore, new information that would normally fit adjacent to existing information cannot be placed near that information as there is no space for it at the desired location on the optical disk. Consequently, an index structure such as an inverted file cannot be changed due to this non-erasable attribute of the storage medium. It is possible to simply create a new file in a new area of the disk but this strategy is very inefficient due to the extreme waste of disk space.
When signature files are used, new information added to the database causes the signature file to increase in size since new entries are appended to the file. Since the existing information in the signature file is not changed the use of these files is of considerable advantage in the optical disk environment.
In many cases, the system responds to a user query by retrieving one or more documents that contain one or more words that the user has specified within that query. To accomplish this, indexing facilities are used to specify the locations of required information in the database. By issuing a list of document identifiers which serve to locate the documents that contain these keywords, the index facilities working in conjunction with the query resolution software determines a final list of documents satisfying the needs of the query.
The use of signature files to locate data in a database is a known strategy. A signature file is a condensation of the information in the database. This is accomplished by representing each distinct word in a document of the database with a word signature. When the system is presented with a particular query word, it will derive the word signature that has been associated with that database word. These types of systems then cause the entire signature file to be searched using a serial scan strategy and, subsequently, based on the results of that search, all documents in the database containing the word can be found. This occurs because any word signature in the signature file is followed by a document identifier for the document that contains the word from which the word signature was derived. Consequently, when a word signature in the signature file matches the word signature derived from the query word, during the scan process, the system will capture the accompanying document identifier in order to retain the identity of documents that are pertinent to the query. These systems can still be very time consuming if the entire signature file is searched for each query word.
Optical disks are the most economical means to store databases. However, seek times for an optical disk are typically four to more than thirty times as long as the seek time for a magnetic hard disk. When databases are searched using the inverted file approach, the system may undertake several probes of the index structure with each probe possibly requiring a disk seek or disk arm movement. When a more expensive magnetic hard disk is used, the time requirements are tolerable but can become extremely undesirable when using an optical disk.
It is an object of the present invention to provide a relatively fast method of data storage and retrieval whereby only a single probe into the signature file is necessary and only part of the signature file is searched in response to a particular query keyword.
In accordance with the present invention, a method of operating a computer system to store and retrieve information in a database wherein the computer system has data processing capability, memory and data storage modules capable of containing data records is as follows:
(a) storing the database on the data storage modules;
(b) during loading, said system automatically creating for the database a signature file which is divided into subsets, mapping a word signature to a particular subset during creation of the file and storing said signature file subsets on said data storage modules;
(c) during retrieval, after the signature file is created, entering at least one query word into the system;
(d) said system automatically creating a signature for each query word entered into the system;
(e) scanning for a word signature and retrieving the corresponding data from said database in response to a query word by using the same mapping information that was used to store the word signature in a particular subset, said system matching the signature of a query word with at least one word signature in one subset of said signature word if such an appropriate word signature exists in this subset.
In the drawings:
FIG. 1 is a diagram of a prior art hardware equipment assemblage with which the present invention can be used;
FIG. 2 is a drawing of an index structure showing three space extents after each subset;
FIG. 3 is a drawing showing that a subset is comprised of many signature groups;
FIG. 4 is a drawing of a signature group having a document identifier following each word signature;
FIG. 5 is a computer programmable process flow diagram illustrating a loading method using the present invention; and
FIG. 6 is a computer programmable process flow diagram illustrating a retrieval method using the present invention.
From FIG. 1, it can be seen that a data storage and retrieval system in accordance with the present invention is designed so that it can be accessed by a number of users simultaneously through user terminals 2, each user searching for different data and using different query words. The system also has a plurality of or data storage modules 4 on which the database is stored and from which the data can be retrieved.
Once the word signatures of the query words are detected in the signature file of the database, the identifiers of all documents containing the corresponding words are collected as a list of candidate documents. If desired, the software can be designed to process this list to determine whether or not a particular document satisfies additional requirements of a query. The user is then informed of the presence of the documents and may retrieve the actual documents for examination if desired.
A signature file is automatically created from the database, and is subsequently stored on the data storage device or optical disk. The signature file contains a sequence of integers (bit strings of fixed length), each integer representing the physical word signature of a significant word contained in the main text of the database. When the signature file for a particular document is automatically created, two steps are followed:
1. Common words are removed using a list of stop words;
2. A logical word signature is computed for each distinct remaining word in the document. This computation maps words (character strings) onto integer values that are m bits long, where m is an integer ranging from 8 to 32. Preferably, each logical word signature is generated so that it has two components, an n-bit physical word signature concatenated to a subset designation field, which selects one of several subsets, where n ranges from 8 to 20;
Stop words are words that generally do not contribute to the processes that serve to discriminate one document from another when the requirements of the query are to be met. They are often connecting words or common articles. For example, common words are "a", "the", "when", "where", "henceforth", etc. A list of stop words is loaded onto the system and the system automatically overlooks the stop words and does not create a word signature for them.
As shown in FIG. 2, each signature file subset, when automatically created during a database load, is a series of document signature groups appearing in the same order as the corresponding text documents (see FIG. 4). Each document signature group is comprised of a series of word signatures derived from the words in the same corresponding text document. The final entry in the signature group for one document is a representation of the identifier of that document (see FIG. 4). When a user query is to be satisfied, query words from the user query are converted into logical signatures and the signature file is scanned for matching physical word signatures. Whenever a match occurs, a representation of a document identifier at the end of the group is extracted so that the corresponding text document can be eventually located. Of course, if an appropriate word signature does not exist in any subset, then no match will occur.
It is possible to generate logical word signatures by using a hash function. This has the advantage of a fast generation and very little memory usage. However there is a drawback: since the hash encoding for a particular word signature is not guaranteed to be a one to one mapping, it is possible that different words map to the same logical word signature. During a scan operation, this multiple map can produce a false drop and an unrelated document of no interest to the user may be retrieved. This can be detected and rectified by having software check documents before they are passed to the user. False drops can be made to occur very infrequently if word signatures are long enough. The signature file can be created by using a hash function that maps words onto integer values formed from a number of bits, and creating representations of the document identifiers that are used to derive pointers to the documents.
Word signatures are usually significantly shorter than the individual text words that they represent. Also, as common words and duplicate signatures are eliminated, the signature file is much smaller than the database from which it is derived. Typically, the length of the signature file is roughly 5% to 60% of the length of the database. If the signature file contains a provision that produces related terms or synonyms that are placed in an abstract prior to the start of a document, the signature file will be somewhat enlarged.
If additional documents are appended to the database, the signature file is similarly extended by appending to the signature file additional word signatures in the form of document signature groups. The fact that the signature file can be easily updated is a distinct advantage to be gained by the use of signature files.
While the scanning of a signature file is much faster than the scanning of the entire database, even the scanning of the signature file can be fairly time consuming, particularly when the data storage device is an optical disk. For example, if a database has a size of 700 megabytes, the signature file will have a size of approximately 35 megabytes. The data streams into the data processing means from the disk at a typical rate of one megabyte per second so any scan of the signature file will take at least 35 seconds.
In order to minimize the scan time for an optical disk while retaining the advantage of an easy update, the signature file is subdivided into a reasonably large number of subsets, (for example, 256 or more subsets). During the creation of the signature file, a word signature is mapped to a particular subset and the same mapping information is used when the subset is scanned for the word signature in response to a query word.
Various word signature formats are possible. The following format will serve as an example: 15 bit physical word signatures are stored in two consecutive bytes on a disk with the most significant bit used as a steering bit, one setting of this bit will signify that this 16-bit word contains a physical word signature while the complementary setting will signify that this 16-bit word serves in the indentification of the document.
Scan time will be considerably reduced since, in response to a query word, it is only necessary to scan a small fraction of the total signature file. Subdivision of the signature file will lead to more total space consumption for the file when compared to signature files that are not subdivided. Since the group of all word signatures for a document is now dispersed across several subsets, a document identifier is needed in every subset that contains a portion of that total group.
If we assume that each two byte word signature is followed by a two byte document pointer, then a word signature, in this worst case, will occupy four bytes. When the signature file is not subdivided, each entry is typically a 24 bit signature that occupies three bytes, excluding document numbers. Thus, the total size of a signature file that has been divided into subsets is no more than one-third larger than a non-subdivided signature file.
If a 700 megabytes, using the example described earlier, the size of the signature file after being subdivided will be an additional 33% or 99.3 megabytes in all. When this subdivided file is spread over 256 subsets, each subset will have an average size of approximately 0.36 megabytes. With a transfer rate of one megabyte per second, an average subset can be transferred in 0.36 seconds.
A signature subset is scanned most effectively if no disk seek is necessary during that scan. This requires that a subset be maintained in contiguous sectors of the disk even though it will grow with the addition of new information. This is done by providing free space between the consecutive subsets as shown in FIG. 2. This free space will be gradually utilized as the database increases in size. When the data storage module is a disk, the data processing means is used to fetch one or more subsets from the disk. The processor looks for pre-specified physical word signatures.
The system helps to ensure the predictable growth of subsets by exercising some care when it decides which subset will hold a particular word signature.
When a word is first encountered in the database it is assigned to the subset which currently has the shortest length. For each subset, the processor keeps track of the highest physical word signature previously assigned. The new entry is given a word signature equal to this maximum plus one. Once the subset identifier is defined and the physical word signature is also defined, the processor will concatentate the two to form the logical word signature which can then be established in the database word dictionary. This involves a two pass scan of the text in the database. During the first pass, the system creates a list of all distinct words in the database keeping track of the number of documents that contain each word. This document count will serve to properly estimate, for each word, the total storage requirements of its word signature groups within a subset. The words are then sorted in ascending order of document counts. It is then a simple matter to assign a subset to the word signature of each word in such a way that the length of the signature subsets are as uniform as possible. This assignation is saved in the word dictionary so that during the second pass through the database, the system will compose logical signatures by concatenating the subset assignment to the physical word signature. When the association between the logical word signature and the corresponding word is retained in a keyword dictionary, the values of the subset designation fields within their logical word signatures are chosen to help in maintaining the uniform lengths of all subsets. The physical word signatures are chosen to ensure a one to one mapping between the logical word signatures and the corresponding word. The physical word signature for a word can be uniquely defined once the system knows which words are associated with a particular subset. This is done by simply numbering the distinct keywords assigned to the subset with consecutive integers. These numbers are taken to be the physical word signatures.
Depending on the application, the system could respond to the user in a variety of ways. When a particular query words is fed into the system, it is expected that the system will search only that subset containing the physical word signature matching the physical word signature of the query word. The subset will contain the document identifiers of all documents in the database that contain that query word. Using the document identifiers the documents can then be retrieved from the database without scanning the entire database.
The number of bits used in a physical word signature can range over a number of possible values depending on the requirements of the system. An n-bit physical word signature is used as an address for a RAM table with two to the power n locations, where n is an integer ranging from 8 to 20. Each location contains one bit and the subset scanning is controlled in such a fashion that it ignores word signatures when the RAM indicates a word signature is of no interest to the query. Otherwise, it places the physical word signature into the FIFO buffer.
In the following embodiment we will assume a length of 15 bits for the physical word signatures. Each 15 bit physical word signature is used as an address for a 32K by one RAM table which has contents previously defined by software running on the central processing unit (henceforth CPU). If the bit location accessed contains a binary value which indicates that this physical word signature is not being sought by this particular query, the physical word signature is ignored. If the bit location accessed contains the complementary value, then the physical word signature and the following document identifier are placed in a first in first out (FIFO) buffer for future reference by the CPU. When a particular physical word signature is ignored, the system proceeds to examine the next physical word signature. The preferred number of bits used in the logical word signature is m-bits in length, where m ranges from 8 to 32.
In the interest of minimizing the disk space utilized by the signature file, the representations of document identifiers should occupy, on average, as little space as possible. One manner in which this can be done, during creation of the signature file, is by treating the document number as a value that is made up of three fields, a high order field labelled H, a middle order field labelled M and a low order field labelled L as follows: ##STR1##
Although the document numbers are not necessarily consecutive, they will occur in ascending order within a particular subset. Therefore, the H or M fields are placed into the next representation of the document identifier only when a lower order field goes through a zero value since the last representation. During a scan operation, the H field is always pushed into the FIFO buffer whenever it is encountered. When an M field appears in the stream, it is saved for future use in a register that will be called the MREG register. The group of word signatures for each document can then be terminated with a single byte containing the L field. The M field is inserted prior to an L field only if the M value has increased beyond the value associated with the previous L field. When a representation of a document identifier is to be entered into the FIFO buffer, it is combined with the last seen M field (the one that was saved in MREG). The software processing the FIFO buffer output will combine M, L pairs with the H field last seen in the stream. In this fashion, references to a document can be handled with a small space overhead that is slightly more than one byte per document group on average. While the representation of the document identifier might be an `L field` only or an `M and L field` only, the actual document identifier always contains all three fields.
Table 1 presents an example of encodings for bytes and words in a signature file subset. In Table 1, LSSA and HSSA represent low order and high order portions of the signature sector address, which is included at the beginning of each sector as a redundent check on the source of the word signature stream.
In more general terms, during creation of the signature file, a series of groups are generated to make up each subset. Each group has a series of physical word signatures and is terminated by a representation of a document identifier. The actual document identifier has a high, middle and low order field. The representation of the document identifier of the first group in the subset actually has a high, middle and low order field. The representations of document identifiers from subsequent groups always have a low order field but only have a middle order field or a high order field when necessary to reflect a change or changes in these fields from the document identifier represented in the immediately prior group. The document identifiers are arranged in ascending order. Thus, while the representation of the document identifier for a particular group might have a low order field only, the actual document identifier, for that group, will have a high, middle and low order field. As a variation, if there was no concern with saving space, all representations of document identifiers could actually have three fields.
TABLE 1__________________________________________________________________________Type of Subset Bit LengthEntry Format of Entry Action to be Taken__________________________________________________________________________Word Signature ##STR2## 16 Push into FIFO if a match is detectedDocument Number L Field ##STR3## 8 Combine with MREG and push into FIFO if a signature in this group is detectedDocument Number M Field ##STR4## 8 Save in MREGDocument Number H Field ##STR5## 16 Push into FIFOLow Order Portion of Signature Sector Address ##STR6## 16 Push into FIFOHigh Order Portion of Signature Sector Address ##STR7## 16 Push into FIFO__________________________________________________________________________
During retrieval of information from the data storage areas, the processor pushes all document identifiers having a high order field into the FIFO buffer. The processor saves the last middle order field encountered in the data stream in a register for future use. The last middle order field encountered is inserted into the FIFO along with the low order field that terminates a particular group only if the RAM has indicated a match between the physical word signature of the query word and a physical word signature in that particular group.
In FIG. 5, there is shown a process flow diagram for loading the database. During the loading of the database, the processor automatically creates a word signature file with document identifiers, the identifiers being used for retrieving a document from the database in response to a query word. During loading, the processor, extracts each word of text and determines whether the word is a common word or not. If the word is a common word, the processor passes the word by. If the word is not a common word, the processor next determines whether the word is in the word dictionary. If the word is not in the word dictionary, the processor finds an identifier for the shortest subset. Next, the processor generates a physical word signature for the word and concatenates the identifier for the subset and the physical word signature to form a logical word signature. Then, the logical word signature is placed in the word dictionary.
If the word is already in the word dictionary, the physical word signature and a representation of the document identifier are placed into the subset designated by the subset identifier by overwriting the previous document identifier if it is the same. Next, it is determined whether the subset is filled. If not, the next word of text of the database is extracted and the process is repeated. If the subset is filled, the subsets are automatically shifted to leave free space for each subset in proportion to the current size of that subset. After the shifting occurs, the next word of the text of the database is extracted and the process is repeated.
In FIG. 6, there is shown a process flow diagram for the retrieval method. During retrieval, the processor first consults the word dictionary to find the subset identifier and physical word signature of the given query word. The processor then starts to scan the designated subset. From the first subset entry, the processor compares the subset entry to the physical word signature of the query word to determine whether or not there is a match. If there is no match, the processor moves onto the next subset entry and repeats the comparison. If there is a match, the processor picks up the representation of the document identifier. If the identifier contains an H field, this is retained for future use. If the identifier contains only the M and L fields, the full representation of the document identifier is generated by concatenating the previously saved H field to the M and L fields. Whenever an M field is part of the representation, it is saved for future use in a register called MREG. If the document identifier encountered during retrieval contains only the L field, it is combined with both of the previously saved H and M fields to obtain the full representation of the identifier. The processor then moves onto the next subset entry and the process is repeated for the entire subset.
The advantage of the method of the present invention over other existing methods such as inverted lists arises from the fast update (database append) activity that it supports. When new information is added to the database index the subsets expand into available space that is provided for this purpose. Since words share subsets the growth of a subset is dependent on the average frequency distribution of its constituent words. This property makes the growth of a subset very predictable. The method reassigns free space, when necessary to the subsets in proportion to their current size. Studies have shown that this predictable expansion promotes a uniform consumption of the free space across almost all subsets during load operations. This improves load performance because the processor does not have to spend time frequently shifting the subsets to maintain their contiguity on the disk due to any subset overflow. The method anticipates that occasionally free space is entirely used up and a subset operation is necessary. The significant improvement of this indexing technique rests on the fact that such a shift occurs only rarely and so load operations are fast since they are mainly the simple insertion of new index information.
Numerous variations, within the scope of the attached claims, will be readily apparent to those skilled in the art.
|Cited Patent||Filing date||Publication date||Applicant||Title|
|US4068301 *||Oct 14, 1975||Jan 10, 1978||Ricoh Company, Ltd.||Data storage device comprising search means|
|US4085446 *||Aug 17, 1976||Apr 18, 1978||Fumitaka Nagamura||Data storage and retrieval system|
|US4255796 *||Feb 14, 1978||Mar 10, 1981||Bell Telephone Laboratories, Incorporated||Associative information retrieval continuously guided by search status feedback|
|US4318184 *||Sep 5, 1978||Mar 2, 1982||Millett Ronald P||Information storage and retrieval system and method|
|US4358824 *||Dec 28, 1979||Nov 9, 1982||International Business Machines Corporation||Office correspondence storage and retrieval system|
|US4554631 *||Jul 13, 1983||Nov 19, 1985||At&T Bell Laboratories||Keyword search automatic limiting method|
|Citing Patent||Filing date||Publication date||Applicant||Title|
|US5148541 *||Nov 3, 1989||Sep 15, 1992||Northern Telecom Limited||Multilingual database system including sorting data using a master universal sort order for all languages|
|US5265065 *||Oct 8, 1991||Nov 23, 1993||West Publishing Company||Method and apparatus for information retrieval from a database by replacing domain specific stemmed phases in a natural language to create a search query|
|US5307266 *||Aug 7, 1991||Apr 26, 1994||Hitachi, Ltd.||Information processing system and method for processing document by using structured keywords|
|US5319745 *||Sep 16, 1992||Jun 7, 1994||Societe Nationale Industrielle Et Aerospatiale||Method and apparatus for processing alphanumeric and graphic information to create a data base|
|US5319779 *||Feb 19, 1992||Jun 7, 1994||International Business Machines Corporation||System for searching information using combinatorial signature derived from bits sets of a base signature|
|US5355476 *||Dec 2, 1991||Oct 11, 1994||Casio Computer Co., Ltd.||File update apparatus for generating a matrix representing a subset of files and the update correspondence between directories and files|
|US5367672 *||Aug 2, 1991||Nov 22, 1994||Kabushiki Kaisha Toshiba||Apparatus for retrieving data using the remainder of a hashed search key to identify a group of keys and comparing the key to the group of keys|
|US5396624 *||Aug 3, 1993||Mar 7, 1995||Visa International Service Association||Account file for off-line transaction authorization|
|US5418948 *||Sep 8, 1993||May 23, 1995||West Publishing Company||Concept matching of natural language queries with a database of document concepts|
|US5423040 *||Jan 14, 1994||Jun 6, 1995||International Business Machines Corporation||System and method for efficiently executing directed acyclic graphs|
|US5535382 *||Nov 17, 1993||Jul 9, 1996||Ricoh Company, Ltd.||Document retrieval system involving ranking of documents in accordance with a degree to which the documents fulfill a retrieval condition corresponding to a user entry|
|US5542090 *||Jul 27, 1994||Jul 30, 1996||Xerox Corporation||Text retrieval method and system using signature of nearby words|
|US5586218 *||Aug 24, 1995||Dec 17, 1996||Inference Corporation||Autonomous learning and reasoning agent|
|US5692176 *||Nov 22, 1993||Nov 25, 1997||Reed Elsevier Inc.||Associative text search and retrieval system|
|US5696963 *||Apr 14, 1995||Dec 9, 1997||Waverley Holdings, Inc.||System, method and computer program product for searching through an individual document and a group of documents|
|US5708829 *||Sep 25, 1996||Jan 13, 1998||Wang Laboratories, Inc.||Text indexing system|
|US5724576 *||Apr 3, 1995||Mar 3, 1998||Prime Arithmetics, Inc.||Method and apparatus for the generation and manipulation of data structures|
|US5742806 *||Jan 31, 1994||Apr 21, 1998||Sun Microsystems, Inc.||Apparatus and method for decomposing database queries for database management system including multiprocessor digital data processing system|
|US5745900 *||Aug 9, 1996||Apr 28, 1998||Digital Equipment Corporation||Method for indexing duplicate database records using a full-record fingerprint|
|US5748953 *||May 18, 1995||May 5, 1998||Hitachi, Ltd.||Document search method wherein stored documents and search queries comprise segmented text data of spaced, nonconsecutive text elements and words segmented by predetermined symbols|
|US5758152 *||Dec 6, 1990||May 26, 1998||Prime Arithmetics, Inc.||Method and apparatus for the generation and manipulation of data structures|
|US5761497 *||Jun 7, 1995||Jun 2, 1998||Reed Elsevier, Inc.||Associative text search and retrieval system that calculates ranking scores and window scores|
|US5771378 *||Jun 7, 1995||Jun 23, 1998||Reed Elsevier, Inc.||Associative text search and retrieval system having a table indicating word position in phrases|
|US5848409 *||Aug 4, 1997||Dec 8, 1998||Smartpatents, Inc.||System, method and computer program product for maintaining group hits tables and document index tables for the purpose of searching through individual documents and groups of documents|
|US5884303 *||Feb 6, 1997||Mar 16, 1999||International Computers Limited||Parallel searching technique|
|US5913209 *||Jul 7, 1997||Jun 15, 1999||Novell, Inc.||Full text index reference compression|
|US5950214 *||Apr 10, 1998||Sep 7, 1999||Aurigin Systems, Inc.||System, method, and computer program product for accessing a note database having subnote information for the purpose of manipulating subnotes linked to portions of documents|
|US5963942 *||Dec 24, 1996||Oct 5, 1999||Fujitsu Limited||Pattern search apparatus and method|
|US5966703 *||Apr 3, 1998||Oct 12, 1999||Digital Equipment Corporation||Technique for indexing information stored as a plurality of records|
|US5970497 *||Apr 27, 1998||Oct 19, 1999||Digital Equipment Corporation||Method for indexing duplicate records of information of a database|
|US5991751 *||Jun 2, 1997||Nov 23, 1999||Smartpatents, Inc.||System, method, and computer program product for patent-centric and group-oriented data processing|
|US5991780 *||Apr 3, 1998||Nov 23, 1999||Aurigin Systems, Inc.||Computer based system, method, and computer program product for selectively displaying patent text and images|
|US6018749 *||Apr 9, 1998||Jan 25, 2000||Aurigin Systems, Inc.||System, method, and computer program product for generating documents using pagination information|
|US6119114 *||Sep 17, 1997||Sep 12, 2000||Smadja; Frank||Method and apparatus for dynamic relevance ranking|
|US6173298||Sep 17, 1997||Jan 9, 2001||Asap, Ltd.||Method and apparatus for implementing a dynamic collocation dictionary|
|US6185559||May 9, 1997||Feb 6, 2001||Hitachi America, Ltd.||Method and apparatus for dynamically counting large itemsets|
|US6216123 *||Jun 24, 1998||Apr 10, 2001||Novell, Inc.||Method and system for rapid retrieval in a full text indexing system|
|US6219818||Feb 18, 1999||Apr 17, 2001||Netmind Technologies, Inc.||Checksum-comparing change-detection tool indicating degree and location of change of internet documents|
|US6339767 *||Aug 29, 1997||Jan 15, 2002||Aurigin Systems, Inc.||Using hyperbolic trees to visualize data generated by patent-centric and group-oriented data processing|
|US6374250 *||Feb 3, 1997||Apr 16, 2002||International Business Machines Corporation||System and method for differential compression of data from a plurality of binary sources|
|US6389434||Apr 9, 1998||May 14, 2002||Aurigin Systems, Inc.||System, method, and computer program product for creating subnotes linked to portions of data objects after entering an annotation mode|
|US6499026||Sep 15, 2000||Dec 24, 2002||Aurigin Systems, Inc.||Using hyperbolic trees to visualize data generated by patent-centric and group-oriented data processing|
|US6687687 *||Jul 26, 2000||Feb 3, 2004||Zix Scm, Inc.||Dynamic indexing information retrieval or filtering system|
|US6728659||Jul 14, 1998||Apr 27, 2004||Tlv Company, Limited||Equipment inspection and evaluation system, equipment management system, and computer-readable record medium with equipment management program stored therein|
|US6772093||Jan 24, 2001||Aug 3, 2004||Tlv Company, Limited||Equipment inspection and evaluation system, equipment management system, and computer-readable record medium with equipment management program stored therein|
|US6850848 *||Jan 24, 2001||Feb 1, 2005||Tlv Company, Limited||Equipment inspection and evaluation system, equipment management system, and computer-readable record medium with equipment management program stored therein|
|US6877137||Dec 7, 1999||Apr 5, 2005||Rose Blush Software Llc||System, method and computer program product for mediating notes and note sub-notes linked or otherwise associated with stored or networked web pages|
|US6880128||Jan 24, 2001||Apr 12, 2005||Tlv Company, Limited|
|US6912655||Aug 9, 1999||Jun 28, 2005||Tristrata Security Inc.||Network security architecture system utilizing seals|
|US6917709 *||Dec 16, 2002||Jul 12, 2005||Parascript Llc||Automated search on cursive records not having an ASCII index|
|US7146376 *||Apr 24, 2003||Dec 5, 2006||International Business Machines Corporation||Data abstraction model driven physical layout|
|US7152074 *||Sep 19, 2003||Dec 19, 2006||International Business Machines Corporation||Extensible framework supporting deposit of heterogenous data sources into a target data repository|
|US7158983||Sep 23, 2002||Jan 2, 2007||Battelle Memorial Institute||Text analysis technique|
|US7257706||May 6, 2005||Aug 14, 2007||Tristrata Security, Inc.||Method of securing a document in a system and controlling access to the document and a seal for use in the method|
|US7487149 *||Mar 10, 2004||Feb 3, 2009||Oracle International Corporation||Method and apparatus for providing query-level security in a database system|
|US7487542||Jan 14, 2004||Feb 3, 2009||International Business Machines Corporation||Intrusion detection using a network processor and a parallel pattern detection engine|
|US7523126||Jun 22, 2002||Apr 21, 2009||Rose Blush Software Llc||Using hyperbolic trees to visualize data generated by patent-centric and group-oriented data processing|
|US7620632||Dec 7, 2004||Nov 17, 2009||Skyler Technology, Inc.||Method and/or system for performing tree matching|
|US7627591||Dec 7, 2004||Dec 1, 2009||Skyler Technology, Inc.||Method and/or system for manipulating tree expressions|
|US7630995||Dec 7, 2004||Dec 8, 2009||Skyler Technology, Inc.||Method and/or system for transmitting and/or receiving data|
|US7636727||Dec 6, 2004||Dec 22, 2009||Skyler Technology, Inc.||Enumeration of trees from finite number of nodes|
|US7676453 *||Apr 22, 2004||Mar 9, 2010||Oracle International Corporation||Partial query caching|
|US7681177||Feb 23, 2006||Mar 16, 2010||Skyler Technology, Inc.||Method and/or system for transforming between trees and strings|
|US7716060||Feb 23, 2001||May 11, 2010||Germeraad Paul B||Patent-related tools and methodology for use in the merger and acquisition process|
|US7734780||Mar 17, 2008||Jun 8, 2010||Microsoft Corporation||Automated response to computer users context|
|US7739255||Sep 1, 2006||Jun 15, 2010||Ma Capital Lllp||System for and method of visual representation and review of media files|
|US7743249||Feb 14, 2007||Jun 22, 2010||Tristrata Security, Inc.||Method of securing a document in a system and controlling access to the document and a seal for use in the method|
|US7779015||Nov 8, 2004||Aug 17, 2010||Microsoft Corporation||Logging and analyzing context attributes|
|US7797336||May 4, 2001||Sep 14, 2010||Tim W Blair||System, method, and computer program product for knowledge management|
|US7801923||Dec 6, 2004||Sep 21, 2010||Robert T. and Virginia T. Jenkins as Trustees of the Jenkins Family Trust||Method and/or system for tagging trees|
|US7877686||Oct 15, 2001||Jan 25, 2011||Microsoft Corporation||Dynamically displaying current status of tasks|
|US7882147||Dec 6, 2004||Feb 1, 2011||Robert T. and Virginia T. Jenkins||File location naming hierarchy|
|US7899821||Apr 26, 2006||Mar 1, 2011||Karl Schiffmann||Manipulation and/or analysis of hierarchical data|
|US7945859||Dec 17, 2008||May 17, 2011||Microsoft Corporation||Interface for exchanging context data|
|US7949581||Sep 7, 2006||May 24, 2011||Patentratings, Llc||Method of determining an obsolescence rate of a technology|
|US7949728||Aug 31, 2006||May 24, 2011||Rose Blush Software Llc||System, method, and computer program product for managing and analyzing intellectual property (IP) related transactions|
|US7962511||Apr 29, 2003||Jun 14, 2011||Patentratings, Llc||Method and system for rating patents and other intangible assets|
|US7966328||Aug 31, 2006||Jun 21, 2011||Rose Blush Software Llc||Patent-related tools and methodology for use in research and development projects|
|US8020104||Jan 11, 2005||Sep 13, 2011||Microsoft Corporation||Contextual responses based on automated learning techniques|
|US8037102||Dec 6, 2004||Oct 11, 2011||Robert T. and Virginia T. Jenkins||Manipulating sets of hierarchical data|
|US8099415 *||Sep 8, 2006||Jan 17, 2012||Simply Hired, Inc.||Method and apparatus for assessing similarity between online job listings|
|US8103665||May 11, 2009||Jan 24, 2012||Microsoft Corporation||Soliciting information based on a computer user's context|
|US8126979||Apr 13, 2010||Feb 28, 2012||Microsoft Corporation||Automated response to computer users context|
|US8181113||Oct 27, 2008||May 15, 2012||Microsoft Corporation||Mediating conflicts in computer users context data|
|US8239945||Dec 14, 2008||Aug 7, 2012||International Business Machines Corporation||Intrusion detection using a network processor and a parallel pattern detection engine|
|US8316059||Dec 27, 2005||Nov 20, 2012||Robert T. and Virginia T. Jenkins||Enumeration of rooted partial subtrees|
|US8346724||Dec 8, 2008||Jan 1, 2013||Microsoft Corporation||Generating and supplying user context data|
|US8356040||Mar 20, 2006||Jan 15, 2013||Robert T. and Virginia T. Jenkins||Method and/or system for transforming between trees and arrays|
|US8443339||Feb 8, 2010||May 14, 2013||Robert T. and Virginia T. Jenkins||Method and/or system for transforming between trees and strings|
|US8489997||May 7, 2010||Jul 16, 2013||Microsoft Corporation||Supplying notifications related to supply and consumption of user context data|
|US8612461||Nov 30, 2009||Dec 17, 2013||Robert T. and Virginia T. Jenkins||Enumeration of trees from finite number of nodes|
|US8615530||Dec 27, 2005||Dec 24, 2013||Robert T. and Virginia T. Jenkins as Trustees for the Jenkins Family Trust||Method and/or system for tree transformation|
|US8626712||Jun 28, 2010||Jan 7, 2014||Microsoft Corporation||Logging and analyzing computer user's context data|
|US8626777||Oct 13, 2009||Jan 7, 2014||Robert T. Jenkins||Method and/or system for manipulating tree expressions|
|US8677248||May 14, 2009||Mar 18, 2014||Microsoft Corporation||Requesting computer user's context data|
|US9002862||Nov 21, 2013||Apr 7, 2015||Robert T. and Virginia T. Jenkins||Enumeration of trees from finite number of nodes|
|US9020961||Sep 24, 2012||Apr 28, 2015||Robert T. and Virginia T. Jenkins||Method or system for transforming between trees and arrays|
|US9043347||Nov 21, 2013||May 26, 2015||Robert T. and Virginia T. Jenkins||Method and/or system for manipulating tree expressions|
|US9077515||Jan 7, 2014||Jul 7, 2015||Robert T. and Virginia T. Jenkins||Method and/or system for transmitting and/or receiving data|
|US9092545||Aug 31, 2006||Jul 28, 2015||Rose Blush Software Llc||Intellectual property asset manager (IPAM) for context processing of data objects|
|US9177003||Sep 9, 2011||Nov 3, 2015||Robert T. and Virginia T. Jenkins||Manipulating sets of heirarchical data|
|US9177349||Apr 22, 2011||Nov 3, 2015||Patentratings, Llc||Method and system for rating patents and other intangible assets|
|US9183306||Jun 30, 2008||Nov 10, 2015||Microsoft Technology Licensing, Llc||Automated selection of appropriate information based on a computer user's context|
|US9330128||Oct 1, 2012||May 3, 2016||Robert T. and Virginia T. Jenkins||Enumeration of rooted partial subtrees|
|US9372555||Jun 27, 2001||Jun 21, 2016||Microsoft Technology Licensing, Llc||Managing interactions between computer users' context models|
|US9411841||Feb 18, 2015||Aug 9, 2016||Robert T. And Virginia T. Jenkins As Trustees Of The Jenkins Family Trust Dated Feb. 8, 2002||Enumeration of trees from finite number of nodes|
|US9425951||May 29, 2015||Aug 23, 2016||Robert T. and Virginia T. Jenkins||Method and/or system for transmitting and/or receiving data|
|US9430512||Mar 2, 2015||Aug 30, 2016||Robert T. and Virginia T. Jenkins||Method and/or system for manipulating tree expressions|
|US9443037 *||Jul 19, 2006||Sep 13, 2016||Microsoft Technology Licensing, Llc||Storing and recalling information to augment human memories|
|US9559917||Jul 15, 2013||Jan 31, 2017||Microsoft Technology Licensing, Llc||Supplying notifications related to supply and consumption of user context data|
|US9563653||Feb 4, 2015||Feb 7, 2017||Robert T. and Virginia T. Jenkins||Method and/or system for transforming between trees and strings|
|US9619551 *||Nov 23, 2015||Apr 11, 2017||Fti Technology Llc||Computer-implemented system and method for generating document groupings for display|
|US9619909||Nov 14, 2016||Apr 11, 2017||Fti Technology Llc||Computer-implemented system and method for generating and placing cluster groups|
|US9646034||Mar 25, 2016||May 9, 2017||Robert T. and Virginia T. Jenkins||Enumeration of rooted partial subtrees|
|US9646107||Dec 7, 2004||May 9, 2017||Robert T. and Virginia T. Jenkins as Trustee of the Jenkins Family Trust||Method and/or system for simplifying tree expressions such as for query reduction|
|US20020099817 *||Jun 27, 2001||Jul 25, 2002||Abbott Kenneth H.||Managing interactions between computer users' context models|
|US20030046307 *||Jun 22, 2002||Mar 6, 2003||Rivette Kevin G.|
|US20030046401 *||Oct 16, 2001||Mar 6, 2003||Abbott Kenneth H.||Dynamically determing appropriate computer user interfaces|
|US20040215629 *||Apr 24, 2003||Oct 28, 2004||International Business Machines Corporation||Data abstraction model driven physical layout|
|US20040220842 *||Apr 29, 2003||Nov 4, 2004||Barney Jonathan A.||Method and system for rating patents and other intangible assets|
|US20050055381 *||Jun 10, 2004||Mar 10, 2005||Amit Ganesh||Active queries filter extraction|
|US20050065952 *||Sep 19, 2003||Mar 24, 2005||International Business Machines Corporation||Extensible framework supporting deposit of heterogenous data sources into a target data repository|
|US20050086243 *||Nov 8, 2004||Apr 21, 2005||Tangis Corporation||Logging and analyzing computer user's context data|
|US20050154916 *||Jan 14, 2004||Jul 14, 2005||International Business Machine Corporation||Intrusion detection using a network processor and a parallel pattern detection engine|
|US20050187900 *||Dec 6, 2004||Aug 25, 2005||Letourneau Jack J.||Manipulating sets of hierarchical data|
|US20050203886 *||Mar 10, 2004||Sep 15, 2005||Wong Daniel M.||Method and apparatus for providing query-level security in a database system|
|US20050240570 *||Apr 22, 2004||Oct 27, 2005||Oracle International Corporation||Partial query caching|
|US20050267908 *||Dec 7, 2004||Dec 1, 2005||Letourneau Jack J||Method and/or system for simplifying tree expressions, such as for pattern matching|
|US20060004817 *||Dec 7, 2004||Jan 5, 2006||Mark Andrews||Method and/or system for performing tree matching|
|US20060015538 *||Dec 6, 2004||Jan 19, 2006||Letourneau Jack J||File location naming hierarchy|
|US20060095442 *||Dec 7, 2004||May 4, 2006||Letourneau Jack J||Method and/or system for manipulating tree expressions|
|US20060123029 *||Dec 7, 2004||Jun 8, 2006||Letourneau Jack J||Method and/or system for transmitting and/or receiving data|
|US20060129582 *||Dec 6, 2004||Jun 15, 2006||Karl Schiffmann||Enumeration of trees from finite number of nodes|
|US20060259498 *||May 11, 2005||Nov 16, 2006||Microsoft Corporation||Signature set content matching|
|US20060259533 *||Feb 23, 2006||Nov 16, 2006||Letourneau Jack J||Method and/or system for transforming between trees and strings|
|US20060271573 *||Mar 20, 2006||Nov 30, 2006||Letourneau Jack J||Method and/or system for tranforming between trees and arrays|
|US20070043459 *||Jul 19, 2006||Feb 22, 2007||Tangis Corporation||Storing and recalling information to augment human memories|
|US20070089067 *||Oct 15, 2001||Apr 19, 2007||Tangis Corporation||Dynamically displaying current status of tasks|
|US20080065630 *||Sep 8, 2006||Mar 13, 2008||Tong Luo||Method and Apparatus for Assessing Similarity Between Online Job Listings|
|US20080071827 *||Sep 1, 2006||Mar 20, 2008||Charles Hengel||System for and method of visual representation and review of media files|
|US20080109305 *||May 3, 2007||May 8, 2008||Ma Capital Lllp||Using internet advertising as a test bed for radio advertisements|
|US20080109409 *||May 3, 2007||May 8, 2008||Ma Capital Lllp||Brokering keywords in radio broadcasts|
|US20080109845 *||May 3, 2007||May 8, 2008||Ma Capital Lllp||System and method for generating advertisements for use in broadcast media|
|US20080313271 *||Mar 17, 2008||Dec 18, 2008||Microsoft Corporation||Automated reponse to computer users context|
|US20090055752 *||Oct 27, 2008||Feb 26, 2009||Microsoft Corporation||Mediating conflicts in computer users context data|
|US20090083214 *||Sep 21, 2007||Mar 26, 2009||Microsoft Corporation||Keyword search over heavy-tailed data and multi-keyword queries|
|US20090094524 *||Dec 17, 2008||Apr 9, 2009||Microsoft Corporation||Interface for exchanging context data|
|US20090254991 *||Dec 14, 2008||Oct 8, 2009||International Business Machines Corporation||Intrusion detection using a network processor and a parallel pattern detection engine|
|US20090259506 *||Apr 13, 2009||Oct 15, 2009||Barney Jonathan A||Method and system for rating patents and other intangible assets|
|US20100094885 *||Oct 5, 2009||Apr 15, 2010||Skyler Technology, Inc.||Method and/or system for performing tree matching|
|US20100094908 *||Oct 13, 2009||Apr 15, 2010||Skyler Technology, Inc.||Method and/or system for manipulating tree expressions|
|US20100191775 *||Nov 30, 2009||Jul 29, 2010||Skyler Technology, Inc.||Enumeration of trees from finite number of nodes|
|US20100205581 *||Feb 8, 2010||Aug 12, 2010||Skyler Technology, Inc.||Method and/or system for transforming between trees and strings|
|US20100211864 *||Apr 28, 2010||Aug 19, 2010||Ma Capital Lllp||System for and method of visual representation and review of media files|
|US20100217862 *||May 7, 2010||Aug 26, 2010||Microsoft Corporation||Supplying notifications related to supply and consumption of user context data|
|US20100318521 *||Jul 2, 2010||Dec 16, 2010||Robert T. and Virginia T. Jenkins as Trustees of the Jenkins Family Trust Dated 2/8/2002||Method and/or system for tagging trees|
|US20160078126 *||Nov 23, 2015||Mar 17, 2016||Fti Technology Llc||Computer-Implemented System And Method For Generating Document Groupings For Display|
|WO1996007148A1 *||Aug 22, 1995||Mar 7, 1996||Kondratiev Andrei Valentinovic||Textual or graphic data transmission system and a consumer information device for the system|
|U.S. Classification||1/1, 707/E17.036, 707/E17.058, 707/E17.009, 707/999.003|
|Cooperative Classification||Y10S707/99933, G06F17/30017, G06F17/30949|
|European Classification||G06F17/30Z1C, G06F17/30E|
|Sep 13, 1994||REMI||Maintenance fee reminder mailed|
|Feb 5, 1995||LAPS||Lapse for failure to pay maintenance fees|
|Apr 18, 1995||FP||Expired due to failure to pay maintenance fee|
Effective date: 19950208